Research of Video Tracking Algorithm Based on the Blob Analysis

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Abstract:

To the video that contains the target, a method is proposed to create the background model based on the mixed Gauss. And the target locating method based on the blob analysis and blob filtering, the anti-noise ability and filter robustness of tracking is improved. The kalman filter and the particle filter are separately used to pass and update the foreground target’s posterior probability distribution. Finally the kalman filter and the particle filter's are compared and that builds the foundation of the further development.

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Periodical:

Advanced Materials Research (Volumes 383-390)

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1185-1189

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November 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Hou Yi-min, Lun Xiang-min, Lan Jian-jun. Research on object Adaboost location algorithm for iamge sequence. Computer Engineering and Applications, 2010, 46(3): 151-153.

Google Scholar

[2] Xu Xiao-xiao, Wang Zhi-ling, Wu Liang, Chen Zong-hai, Vision tracking algorithm under occlusion of multiple objects, Control and Decision, Vol. 25 No. 2.

Google Scholar

[3] Wang Yu-Ru, Liu Jia-Feng, Liu Guo-Jun, Tang Xiang-Long, Liu Peng, People Tracking Based on Multi-regions Joint Particle Filters. Acta Automatica Sinca, Vol. 35, No. 11 Novermber, (2009).

DOI: 10.3724/sp.j.1004.2009.01387

Google Scholar

[4] Huazhong Ning, Model-Based Tracking of Walking People, Dissertation Submitted to Institute of Automation, Chinese Academy of Sciences in partial fulfillment of the requirements for the degree of Master of Engineering.

Google Scholar

[5] Wang Liang, Hu weiming, Tan tie niu, A survery of Visual Analysis of Human Motion, Chinese Journal of Computers, Vol 03. (2002).

Google Scholar

[6] Han Zhen-jun, Feature Evaluation for Adaptive Visual Object Tracking, Dissertation, (2008).

Google Scholar

[7] P. KaewTraKulPong and R. Bowden, An Improved Adaptive Background Mixture Model for RealtimeTracking with Shadow Detection, In Proc. 2nd European Workshop on Advanced Video Based Surveillance Systems, AVBS01. Sept (2001).

DOI: 10.1007/978-1-4615-0913-4_11

Google Scholar

[8] Zhiyu Zhu, Particle Filters algorithm and it's Applications, , Science Press, (2010).

Google Scholar